Source code for pySAXS.models.PorodC
from model import Model
from pySAXS.LS.LSsca import Qlogspace
import numpy
[docs]class PorodC(Model):
'''
Porod Curved
for Spheres poly-Gauss Model
by OT 10/06/2009
'''
[docs] def PorodCFunction(self,q,par):
"""
Porod model to fit q-4 part at high q
par[0] : Scattering lenght density contrast in cm-2
par[1] : S/V cm-1
par[2] : principal curvature 1 cm-1
par[3] : Principal curvature 2 cm-1
"""
return 2.0*numpy.pi*1.0e-32*par[0]*par[0]*par[1]*q**-4.0*(1.0+1e-16*q**-2.0*(((par[2]+par[3])**2.)/4.+((par[2]-par[3])**2.)/8.))
'''
parameters definition
class Model(7,Porod,/
Qlogspace(1e-4,1.,500.),(
[1.0e10,1e6]),
("Scattering contrast (cm-2)",
"S/V (cm-1)"),("%1.3e","%1.3e"),
(True,True)),
from LSsca
'''
IntensityFunc=PorodCFunction #function
N=0
q=Qlogspace(1e-4,1.,500.) #q range(x scale)
Arg=[1.0e10,1e6,1e-2,1e-2] #list of defaults parameters
Format=["%1.3e","%1.3e","%1.3e","%1.3e"] #list of c format
istofit=[True,True,True,True] #list of boolean for fitting
name="Porod with curvature correction" #name of the model
Doc=["Scattering contrast (cm-2)","S/V (cm-1)","C1","C2"] #list of description for parameters
if __name__=="__main__":
'''
test code
'''
modl=PorodC()
#plot the model
import Gnuplot
gp=Gnuplot.Gnuplot()
gp("set logscale xy")
c=Gnuplot.Data(modl.q,modl.getIntensity(),with_='points')
gp.plot(c)
raw_input("enter")
#plot and fit the noisy model
yn=modl.getNoisy(0.4)
cn=Gnuplot.Data(modl.q,yn,with_='points')
res=modl.fit(yn)
cf=Gnuplot.Data(modl.q,modl.IntensityFunc(modl.q,res),with_='lines')
gp.plot(c,cn,cf)
raw_input("enter")
#plot and fit the noisy model with fitBounds
bounds=modl.getBoundsFromParam() #[250.0,2e11,1e10,1.5e15]
res2=modl.fitBounds(yn,bounds)
print res2
raw_input("enter")